Users, manufacturers and resellers of computing devices often desire to analyze the performance of a computing device. For example, manufacturers can desire to analyze the performance of computing devices, prior to being shipped from the manufacturing facility, to detect anomalies that can signify manufacturing errors, or that can differentiate higher performance components from lower performance components, thereby enabling the manufacturer to charge a higher price for the higher performance components. Similarly, resellers of computing devices can desire to analyze their performance as part of a sales effort, such as advertising or marketing to potential consumers. Users of computing devices may have multiple reasons for desiring to analyze the performance of their computing devices. For example, enthusiast users may seek to optimize the performance of their computing device, and may exchange performance analysis data among other like-minded enthusiast users. As another example, users may seek to analyze the performance of their computing devices to detect problems or to quantify issues that the user may be experiencing so that those issues can be analyzed further, such as by dedicated technical support professionals.
Traditionally, the performance of a computing device has been quantified by independent performance measurement application programs that execute a pre-defined suite, and often a standardized suite, of performance quantifying tasks. The results are typically presented in the form of numerical data that is often standardized by reference to a well known computing device or component. However, most users may not have ever had any experience with the device or component to which the results are standardized and, consequently, the returned results have no meaning to such users. And while users may be able to compare results with one another at a high level, such as by e-mailing the numerical values reported by their performance measurement application programs, there is no mechanism by which a comparison between multiple computing devices that focuses on the raw, underlying data can be made. Additionally, many standardized suites of performance quantifying tasks may focus only the hardware of a computing device and, consequently, may never detect software anomalies. For example, a computing device with one or more corrupted, or incompatible, data files may be perceived by a user to start up slowly even if a standardized suite of performance quantifying tasks indicates that the hardware of such a computing device is operating properly.